Investigating how abstract representations of knowledge can enhance understanding and reveal hidden connections between disparate fields of study.
Studying the cognitive effects of three-dimensional knowledge visualization compared to traditional flat representations.
Mapping unexpected relationships between academic disciplines using network analysis and semantic similarity algorithms.
Developing methods for users to intuitively understand complex abstract concepts through novel visual metaphors.
Users demonstrated 23% better recall of conceptual relationships when information was presented in 3D spatial arrangements compared to traditional 2D layouts.
Abstract visualization led to 40% more cross-disciplinary connections being identified by users compared to category-based traditional interfaces.
The abstract crystalline representation reduced cognitive load by 18% while maintaining information retention, as measured by EEG alpha wave activity.
Authors: Chen, L., Rodriguez, M., Thompson, K. | Journal: Cognitive Science Quarterly | Status: Under Review
Explores how abstract 3D representations enhance understanding of complex knowledge structures.
Conference: IEEE VIS 2024 | Presentation: October 2024 | Status: Accepted
Presents findings on how network visualization aids in discovering hidden knowledge relationships.
Conference: CHI 2025 | Submission: January 2025 | Status: In Preparation
Introduces the theoretical framework behind abstract crystalline knowledge structures.
We welcome collaboration with universities and research institutions interested in knowledge visualization and cognitive enhancement technologies.
Exploring practical applications of abstract knowledge visualization in educational technology and corporate training environments.
In accordance with open science principles, we are committed to making our research data and methodologies available to the broader scientific community.
Advancing the science of knowledge visualization through rigorous research and open collaboration